# L3CubeMahaSent: A Marathi Tweet-based Sentiment Analysis Dataset

arXiv: https://arxiv.org/abs/2103.11408 · HTML: https://mlsanity.com/paper/2103.11408/

## Key facts

- Cited by 31 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 34 references that are in the map.
- First posted on arXiv 21 Mar 2021.

## Builds on (most cited first, 13 of 13)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Convolutional Neural Networks for Sentence Classification](https://mlsanity.com/paper/1408.5882/) (2014)
- [How to Fine-Tune BERT for Text Classification?](https://mlsanity.com/paper/1905.05583/) (2019)
- [Advances in Pre-Training Distributed Word Representations](https://mlsanity.com/paper/1712.09405/) (2017)
- [Text Classification Algorithms: A Survey](https://mlsanity.com/paper/1904.08067/) (2019)
- [Spread of hate speech in online social media](https://mlsanity.com/paper/1812.01693/) (2018)
- [Hostility Detection Dataset in Hindi](https://mlsanity.com/paper/2011.03588/) (2020)
- [Sentiment Analysis of Code-Mixed Indian Languages: An Overview of SAIL_Code-Mixed Shared Task @ICON-2017](https://mlsanity.com/paper/1803.06745/) (2018)
- [iNLTK: Natural Language Toolkit for Indic Languages](https://mlsanity.com/paper/2009.12534/) (2020)
- [Deep Learning for Hindi Text Classification: A Comparison](https://mlsanity.com/paper/2001.10340/) (2020)
- [Experimental Evaluation of Deep Learning models for Marathi Text Classification](https://mlsanity.com/paper/2101.04899/) (2021)
- [Evaluating Deep Learning Approaches for Covid19 Fake News Detection](https://mlsanity.com/paper/2101.04012/) (2021)
- [Evaluation of Deep Learning Models for Hostility Detection in Hindi Text](https://mlsanity.com/paper/2101.04144/) (2021)

## Built on by (most cited first, 30 of 31)

- [L3Cube-MahaCorpus and MahaBERT: Marathi Monolingual Corpus, Marathi BERT Language Models, and Resources](https://mlsanity.com/paper/2202.01159/) (2022)
- [L3Cube-HindBERT and DevBERT: Pre-Trained BERT Transformer models for Devanagari based Hindi and Marathi Languages](https://mlsanity.com/paper/2211.11418/) (2022)
- [L3Cube-MahaNLP: Marathi Natural Language Processing Datasets, Models, and Library](https://mlsanity.com/paper/2205.14728/) (2022)
- [L3Cube-MahaHate: A Tweet-based Marathi Hate Speech Detection Dataset and BERT models](https://mlsanity.com/paper/2203.13778/) (2022)
- [L3Cube-MahaNER: A Marathi Named Entity Recognition Dataset and BERT models](https://mlsanity.com/paper/2204.06029/) (2022)
- [Hate and Offensive Speech Detection in Hindi and Marathi](https://mlsanity.com/paper/2110.12200/) (2021)
- [Mono vs Multilingual BERT for Hate Speech Detection and Text Classification: A Case Study in Marathi](https://mlsanity.com/paper/2204.08669/) (2022)
- [On Limitations of LLM as Annotator for Low Resource Languages](https://mlsanity.com/paper/2411.17637/) (2024)
- [L3Cube-MahaSBERT and HindSBERT: Sentence BERT Models and Benchmarking BERT Sentence Representations for Hindi and Marathi](https://mlsanity.com/paper/2211.11187/) (2022)
- [L3Cube-MahaSent-MD: A Multi-domain Marathi Sentiment Analysis Dataset and Transformer Models](https://mlsanity.com/paper/2306.13888/) (2023)
- [L3Cube-MahaNews: News-based Short Text and Long Document Classification Datasets in Marathi](https://mlsanity.com/paper/2404.18216/) (2024)
- [Mono vs Multilingual BERT: A Case Study in Hindi and Marathi Named Entity Recognition](https://mlsanity.com/paper/2203.12907/) (2022)
- [Chain-of-Translation Prompting (CoTR): A Novel Prompting Technique for Low Resource Languages](https://mlsanity.com/paper/2409.04512/) (2024)
- [The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languages](https://mlsanity.com/paper/2310.14557/) (2023)
- [mahaNLP: A Marathi Natural Language Processing Library](https://mlsanity.com/paper/2311.02579/) (2023)
- [NLPineers@ NLU of Devanagari Script Languages 2025: Hate Speech Detection using Ensembling of BERT-based models](https://mlsanity.com/paper/2412.08163/) (2024)
- [On Sensitivity of Deep Learning Based Text Classification Algorithms to Practical Input Perturbations](https://mlsanity.com/paper/2201.00318/) (2022)
- [My Boli: Code-mixed Marathi-English Corpora, Pretrained Language Models and Evaluation Benchmarks](https://mlsanity.com/paper/2306.14030/) (2023)
- [Robust Sentiment Analysis for Low Resource languages Using Data Augmentation Approaches: A Case Study in Marathi](https://mlsanity.com/paper/2310.00734/) (2023)
- [L3Cube-MahaSocialNER: A Social Media based Marathi NER Dataset and BERT models](https://mlsanity.com/paper/2401.00170/) (2023)
- [Dynamic Hedging Strategies in Derivatives Markets with LLM-Driven Sentiment and News Analytics](https://mlsanity.com/paper/2504.04295/) (2025)
- [L3Cube-MahaEmotions: A Marathi Emotion Recognition Dataset with Synthetic Annotations using CoTR prompting and Large Language Models](https://mlsanity.com/paper/2506.00863/) (2025)
- [MaCmS: Magahi Code-mixed Dataset for Sentiment Analysis](https://mlsanity.com/paper/2403.04639/) (2024)
- [BhashaSutra: A Task-Centric Unified Survey of Indian NLP Datasets, Corpora, and Resources](https://mlsanity.com/paper/2604.18423/) (2026)
- [Leveraging Parameter Efficient Training Methods for Low Resource Text Classification: A Case Study in Marathi](https://mlsanity.com/paper/2408.03172/) (2024)
- [1-800-SHARED-TASKS @ NLU of Devanagari Script Languages: Detection of Language, Hate Speech, and Targets using LLMs](https://mlsanity.com/paper/2411.06850/) (2024)
- [IITR-CIOL@NLU of Devanagari Script Languages 2025: Multilingual Hate Speech Detection and Target Identification in Devanagari-Scripted Languages](https://mlsanity.com/paper/2412.17947/) (2024)
- [Human-Centered Supervision for Sentiment Analysis in Telugu: A Systematic Inquiry Beyond Accuracy](https://mlsanity.com/paper/2508.01486/) (2025)
- [L3Cube-MahaPOS: A Marathi Part-of-Speech Tagging Dataset and BERT Models](https://mlsanity.com/paper/2606.24825/) (2026)
- [Enhancing Zero-Shot Domain Transfer in Low-Resource Sentiment Analysis: A Case Study in Marathi](https://mlsanity.com/paper/2610.15757/) (2026)

## Abstract (arXiv)

Sentiment analysis is one of the most fundamental tasks in Natural Language Processing. Popular languages like English, Arabic, Russian, Mandarin, and also Indian languages such as Hindi, Bengali, Tamil have seen a significant amount of work in this area. However, the Marathi language which is the third most popular language in India still lags behind due to the absence of proper datasets. In this paper, we present the first major publicly available Marathi Sentiment Analysis Dataset - L3CubeMahaSent. It is curated using tweets extracted from various Maharashtrian personalities' Twitter accounts. Our dataset consists of ~16,000 distinct tweets classified in three broad classes viz. positive, negative, and neutral. We also present the guidelines using which we annotated the tweets. Finally, we present the statistics of our dataset and baseline classification results using CNN, LSTM, ULMFiT, and BERT-based deep learning models.